65 resultados para Complex system


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The study of models for ``metal-enzyme-substrate'' interaction has been a proactive area of research owing to its biological and pharmacological importance. In this regard the ternary copper uracil complex with 1,10-phenanthroline represents metal-enzyme-substrate system for DNA binding enzymes. The synthesis of the complex, followed by slow evaporation of the reaction mixture forms two concomitant solvatomorph crystals viz., {Cu(phen)(mu-ura)(H2O)](n)center dot H2O (1a)} and {Cu(phen)(mu-ura)(H2O)](n)center dot CH3OH (1b)}. Both complexes are structurally characterized, while elemental analysis, IR and EPR spectra were recorded for 1b (major product). In both complexes, uracil coordinates uniquely via N1 and N3 nitrogen atom acting as a bidentate bridging ligand forming a 1-D polymer. The two solvatomorphs were quantitatively analyzed for the differences with the aid of Hirshfeld surface analysis. (C) 2014 Elsevier B.V. All rights reserved.

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3-Dimensional Diffuse Optical Tomographic (3-D DOT) image reconstruction algorithm is computationally complex and requires excessive matrix computations and thus hampers reconstruction in real time. In this paper, we present near real time 3D DOT image reconstruction that is based on Broyden approach for updating Jacobian matrix. The Broyden method simplifies the algorithm by avoiding re-computation of the Jacobian matrix in each iteration. We have developed CPU and heterogeneous CPU/GPU code for 3D DOT image reconstruction in C and MatLab programming platform. We have used Compute Unified Device Architecture (CUDA) programming framework and CUDA linear algebra library (CULA) to utilize the massively parallel computational power of GPUs (NVIDIA Tesla K20c). The computation time achieved for C program based implementation for a CPU/GPU system for 3 planes measurement and FEM mesh size of 19172 tetrahedral elements is 806 milliseconds for an iteration.

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We describe a group of alloys with ultrahigh strength of about 2 GPa at 700 degrees C and exceptional oxidation resistance to 1100 degrees C. These alloys exploit intermetallic phases with stable oxide forming elements that combine to form fine nanometric scale structures through eutectic transformations in ternary systems. The alloys offer engineering tensile plasticity of about 4% at room temperature though both conventional dislocation mechanisms and twinning in the more complex intermetallic constituent, along with slip lengths that are restricted by the interphase boundaries in the eutectics.

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Formic acid, the simplest carboxylic acid, is found in nature or can be easily synthesized in the laboratory (major by-product of some second generation biorefinery processes); it is also an important chemical due to its myriad applications in pharmaceuticals and industry. In recent years, formic acid has been used as an important fuel either without reformation (in direct formic acid fuel cells, DFAFCs) or with reformation (as a potential chemical hydrogen storage material). Owing to the better efficiency of DFAFCs compared to several other PEMFCs and reversible hydrogen storage systems, formic acid could serve as one of the better fuels for portable devices, vehicles and other energy-related applications in the future. This perspective is focused on recent developments in the use of formic acid as a reversible source for hydrogen storage. Recent developments in this direction will likely give access to a variety of low-cost and highly efficient rechargeable hydrogen fuel cells within the next few years by the use of suitable homogeneous metal complex/heterogeneous metal nanoparticle-based catalysts under ambient reaction conditions. The production of formic acid from atmospheric CO2 (a greenhouse gas) will decrease the CO2 content and may be helpful in reducing global warming.

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There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies.